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1

Compton, E. Conrad. Evaluation of a standard test method for total hemispherical emittance of surfaces from 293 K to 1673 K. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1986.

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2

Feakin, Stephanie J. Biotreatment of surface waters to remove s-triazine herbicides: FR/K 0002, June, 1994. Marlow, Buckinghamshire: Foundation for Water Research, 1994.

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3

Symposium K on Coating and Surface Modifications ro Furface Protection and Tribological Applications (1997 Strasbourg, France). Coatings and surface modifications for surface protection and triboligical applications: Proceedings of Symposium K on Coatings and Surface Modifications for Surface Protection and Tribological Applications of the 1997 ICAM/E-MRS Spring Conference, Strasbourg, France, June 16-20, 1997. Amsterdam: Elsevier, 1997.

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4

Beneath the surface: The hidden realities of teaching culturally and linguistically diverse young learners, K-6. Portsmouth, NH: Heinemann, 2008.

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5

Johnsen, Trygve. K3 Projective models in scrolls. Berlin: Springer, 2004.

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6

Johnsen, Trygve. K3 Projective models in scrolls. Berlin: Springer, 2004.

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7

Sommerfeld, Peter Karl Heinrich. On helium ions underneath the surface of superfluid helium-4 in the temperature range 10mK[less thanor equal to]T[less than or equal to]K. Birmingham: University of Birmingham, 1992.

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8

Bauer, Ingrid C. Surfaces with K℗=7 and pg̳=4 / c Ingrid C. Bauer. Providence, R.I: American Mathematical Society, 2001.

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9

Sharir, Micha. On k-sets in arrangements of curves and surfaces. New York: Courant Institute of Mathematical Sciences, New York University, 1989.

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10

A, Smirnov A. Teorii͡a︡ fazovykh prevrashcheniĭ i razmeshchenii͡a︡ atomov v splavakh vnedrenii͡a︡: S primenenii͡a︡mi k sistemam metall-vodorod. Kiev: Nauk. dumka, 1992.

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11

Kodaira, Kunihiko, Walter L. Baily, and T. Shioda. Complex analysis and algebraic geometry: A collection of papers dedicated to K. Kodaira. Cambridge, Eng: Cambridge University Press, 2008.

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12

Radzevich, S. P. CAD/CAM of sculptured surfaces on multi-axis NC machine: The DG/K-based approach. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2008.

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13

editor, Donagi Ron, Katz Sheldon 1956 editor, Klemm Albrecht 1960 editor, and Morrison, David R., 1955- editor, eds. String-Math 2012: July 16-21, 2012, Universität Bonn, Bonn, Germany. Providence, Rhode Island: American Mathematical Society, 2015.

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14

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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15

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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16

Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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17

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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18

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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19

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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20

Environmental Technology Laboratory (Environmental Research Laboratories), ed. Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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21

Delta-k acoustic sensing of ocean surface waves. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Environmental Technology Laboratory, 1997.

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22

M, Imamura, and United States. National Aeronautics and Space Administration., eds. Measurements of proton-induced production cross sections for ³⁶Cl from Ca and K. [Washington, DC: National Aeronautics and Space Administration, 1998.

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23

Everett, D. H., and R. H. Ottewill. Surface Area Determination: Proceedings of the International Symposium on Surface Area Determination Held at the School of Chemistry, University of Bristol, U. K. , 16--18 July 1969. Elsevier Science & Technology Books, 2013.

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24

K3 Surfaces and Their Moduli. Birkhäuser, 2016.

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25

Geer, Gerard van der, Gavril Farkas, and Carel Faber. K3 Surfaces and Their Moduli. Birkhäuser, 2018.

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26

Geer, Gerard van der, Gavril Farkas, and Carel Faber. K3 Surfaces and Their Moduli. Birkhauser Verlag, 2016.

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27

Henriksen, Niels Engholm, and Flemming Yssing Hansen. Rate Constants, Reactive Flux. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805014.003.0005.

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This chapter discusses a direct approach to the calculation of the rate constant k(T) that bypasses the detailed state-to-state reaction cross-sections. The method is based on the calculation of the reactive flux across a dividing surface on the potential energy surface. Versions based on classical as well as quantum mechanics are described. The classical version and its relation to Wigner’s variational theorem and recrossings of the dividing surface is discussed. Neglecting recrossings, an approximate result based on the calculation of the classical one-way flux from reactants to products is considered. Recrossings can subsequently be included via a transmission coefficient. An alternative exact expression is formulated based on a canonical average of the flux time-correlation function. It concludes with the quantum mechanical definition of the flux operator and the derivation of a relation between the rate constant and a flux correlation function.
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28

International Conference on Gears 2019. VDI Verlag, 2019. http://dx.doi.org/10.51202/9783181023556.

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Der Bericht ist ausschließlich als PDF-Dokument erschienen! Drei Konferenzen in einer, auf 1.874 Seiten finden Sie jede Menge aller neueste Informationen zum Thema Gears. Die beiden anderen Konferenzen waren: 3rd International Conference on High Performance Plastic Gears 2019 und 3rd International Conference on Gear Production 2019 Achtung: Dieser VDI-Bericht ist ausschließlich als PDF-Datei auf CD-ROM lieferbar! Auszug aus dem 22-seitigen Inhaltsverzeichnis: Foreword 1 K. Stahl, Technische Universität München (TUM), Garching International Conference on Gears 2019 Flank strength Influence of gear surface roughness on pitting and micropitting life 3 E. Bergstedt, Prof. U. Olofsson, KTH, Stockholm, Sweden; J. Lin, Beijing University of Technology, Beijing, China; P. Lindholm, ABB Corporate Research, Västerås, Sweden Influence of stressed volume of tooth flank on the surface durability 15 A. Kubo, Research Institute for Applied Sciences, Ooicho, Kyoto, Japan Transfer of the tooth fl...
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29

Horing, Norman J. Morgenstern. Random Phase Approximation Plasma Phenomenology, Semiclassical and Hydrodynamic Models; Electrodynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0010.

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Chapter 10 reviews both homogeneous and inhomogeneous quantum plasma dielectric response phenomenology starting with the RPA polarizability ring diagram in terms of thermal Green’s functions, also energy eigenfunctions. The homogeneous dynamic, non-local inverse dielectric screening functions (K) are exhibited for 3D, 2D, and 1D, encompassing the non-local plasmon spectra and static shielding (e.g. Friedel oscillations and Debye-Thomas-Fermi shielding). The role of a quantizing magnetic field in K is reviewed. Analytically simpler models are described: the semiclassical and classical limits and the hydrodynamic model, including surface plasmons. Exchange and correlation energies are discussed. The van der Waals interaction of two neutral polarizable systems (e.g. physisorption) is described by their individual two-particle Green’s functions: It devolves upon the role of the dynamic, non-local plasma image potential due to screening. The inverse dielectric screening function K also plays a central role in energy loss spectroscopy. Chapter 10 introduces electromagnetic dyadic Green’s functions and the inverse dielectric tensor; also the RPA dynamic, non-local conductivity tensor with application to a planar quantum well. Kramers–Krönig relations are discussed. Determination of electromagnetic response of a compound nanostructure system having several nanostructured parts is discussed, with applications to a quantum well in bulk plasma and also to a superlattice, resulting in coupled plasmon spectra and polaritons.
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30

Bridges, John C. Evolution of the Martian Crust. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190647926.013.18.

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This is an advance summary of a forthcoming article in the Oxford Encyclopedia of Planetary Science. Please check back later for the full article.Mars, which has a tenth of the mass of Earth, has cooled as a single lithospheric plate. Current topography gravity maps and magnetic maps do not show signs of the plate tectonics processes that have shaped the Earth’s surface. Instead, Mars has been shaped by the effects of meteorite bombardment, igneous activity, and sedimentary—including aqueous—processes. Mars also contains enormous igneous centers—Tharsis and Elysium, with other shield volcanoes in the ancient highlands. In fact, the planet has been volcanically active for nearly all of its 4.5 Gyr history, and crater counts in the Northern Lowlands suggest that may have extended to within the last tens of millions of years. Our knowledge of the composition of the igneous rocks on Mars is informed by over 100 Martian meteorites and the results from landers and orbiters. These show dominantly tholeiitic basaltic compositions derived by melting of a relatively K, Fe-rich mantle compared to that of the Earth. However, recent meteorite and lander results reveal considerable diversity, including more silica-rich and alkaline igneous activity. These show the importance of a range of processes including crystal fractionation, partial melting, and possibly mantle metasomatism and crustal contamination of magmas. The figures and plots of compositional data from meteorites and landers show the range of compositions with comparisons to other planetary basalts (Earth, Moon, Venus). A notable feature of Martian igneous rocks is the apparent absence of amphibole. This is one of the clues that the Martian mantle had a very low water content when compared to that of Earth.The Martian crust, however, has undergone hydrothermal alteration, with impact as an important heat source. This is shown by SNC analyses of secondary minerals and Near Infra-Red analyses from orbit. The associated water may be endogenous.Our view of the Martian crust has changed since Viking landers touched down on the planet in 1976: from one almost entirely dominated by basaltic flows to one where much of the ancient highlands, particularly in ancient craters, is covered by km deep sedimentary deposits that record changing environmental conditions from ancient to recent Mars. The composition of these sediments—including, notably, the MSL Curiosity Rover results—reveal an ancient Mars where physical weathering of basaltic and fractionated igneous source material has dominated over extensive chemical weathering.
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31

Skiba, Grzegorz. Fizjologiczne, żywieniowe i genetyczne uwarunkowania właściwości kości rosnących świń. The Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences, 2020. http://dx.doi.org/10.22358/mono_gs_2020.

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Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones are a tissue that even in adult life retains the ability to change shape and structure depending on changes in their mechanical and hormonal environment, as well as self-renewal and repair capabilities. This process is called bone turnover. The basic processes of bone turnover are: • bone modeling (incessantly changes in bone shape during individual growth) following resorption and tissue formation at various locations (e.g. bone marrow formation) to increase mass and skeletal morphology. This process occurs in the bones of growing individuals and stops after reaching puberty • bone remodeling (processes involve in maintaining bone tissue by resorbing and replacing old bone tissue with new tissue in the same place, e.g. repairing micro fractures). It is a process involving the removal and internal remodeling of existing bone and is responsible for maintaining tissue mass and architecture of mature bones. Bone turnover is regulated by two types of transformation: • osteoclastogenesis, i.e. formation of cells responsible for bone resorption • osteoblastogenesis, i.e. formation of cells responsible for bone formation (bone matrix synthesis and mineralization) Bone maturity can be defined as the completion of basic structural development and mineralization leading to maximum mass and optimal mechanical strength. The highest rate of increase in pig bone mass is observed in the first twelve weeks after birth. This period of growth is considered crucial for optimizing the growth of the skeleton of pigs, because the degree of bone mineralization in later life stages (adulthood) depends largely on the amount of bone minerals accumulated in the early stages of their growth. The development of the technique allows to determine the condition of the skeletal system (or individual bones) in living animals by methods used in human medicine, or after their slaughter. For in vivo determination of bone properties, Abstract 10 double energy X-ray absorptiometry or computed tomography scanning techniques are used. Both methods allow the quantification of mineral content and bone mineral density. The most important property from a practical point of view is the bone’s bending strength, which is directly determined by the maximum bending force. The most important factors affecting bone strength are: • age (growth period), • gender and the associated hormonal balance, • genotype and modification of genes responsible for bone growth • chemical composition of the body (protein and fat content, and the proportion between these components), • physical activity and related bone load, • nutritional factors: – protein intake influencing synthesis of organic matrix of bone, – content of minerals in the feed (CA, P, Zn, Ca/P, Mg, Mn, Na, Cl, K, Cu ratio) influencing synthesis of the inorganic matrix of bone, – mineral/protein ratio in the diet (Ca/protein, P/protein, Zn/protein) – feed energy concentration, – energy source (content of saturated fatty acids - SFA, content of polyun saturated fatty acids - PUFA, in particular ALA, EPA, DPA, DHA), – feed additives, in particular: enzymes (e.g. phytase releasing of minerals bounded in phytin complexes), probiotics and prebiotics (e.g. inulin improving the function of the digestive tract by increasing absorption of nutrients), – vitamin content that regulate metabolism and biochemical changes occurring in bone tissue (e.g. vitamin D3, B6, C and K). This study was based on the results of research experiments from available literature, and studies on growing pigs carried out at the Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences. The tests were performed in total on 300 pigs of Duroc, Pietrain, Puławska breeds, line 990 and hybrids (Great White × Duroc, Great White × Landrace), PIC pigs, slaughtered at different body weight during the growth period from 15 to 130 kg. Bones for biomechanical tests were collected after slaughter from each pig. Their length, mass and volume were determined. Based on these measurements, the specific weight (density, g/cm3) was calculated. Then each bone was cut in the middle of the shaft and the outer and inner diameters were measured both horizontally and vertically. Based on these measurements, the following indicators were calculated: • cortical thickness, • cortical surface, • cortical index. Abstract 11 Bone strength was tested by a three-point bending test. The obtained data enabled the determination of: • bending force (the magnitude of the maximum force at which disintegration and disruption of bone structure occurs), • strength (the amount of maximum force needed to break/crack of bone), • stiffness (quotient of the force acting on the bone and the amount of displacement occurring under the influence of this force). Investigation of changes in physical and biomechanical features of bones during growth was performed on pigs of the synthetic 990 line growing from 15 to 130 kg body weight. The animals were slaughtered successively at a body weight of 15, 30, 40, 50, 70, 90, 110 and 130 kg. After slaughter, the following bones were separated from the right half-carcass: humerus, 3rd and 4th metatarsal bone, femur, tibia and fibula as well as 3rd and 4th metatarsal bone. The features of bones were determined using methods described in the methodology. Describing bone growth with the Gompertz equation, it was found that the earliest slowdown of bone growth curve was observed for metacarpal and metatarsal bones. This means that these bones matured the most quickly. The established data also indicate that the rib is the slowest maturing bone. The femur, humerus, tibia and fibula were between the values of these features for the metatarsal, metacarpal and rib bones. The rate of increase in bone mass and length differed significantly between the examined bones, but in all cases it was lower (coefficient b <1) than the growth rate of the whole body of the animal. The fastest growth rate was estimated for the rib mass (coefficient b = 0.93). Among the long bones, the humerus (coefficient b = 0.81) was characterized by the fastest rate of weight gain, however femur the smallest (coefficient b = 0.71). The lowest rate of bone mass increase was observed in the foot bones, with the metacarpal bones having a slightly higher value of coefficient b than the metatarsal bones (0.67 vs 0.62). The third bone had a lower growth rate than the fourth bone, regardless of whether they were metatarsal or metacarpal. The value of the bending force increased as the animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. The rate of change in the value of this indicator increased at a similar rate as the body weight changes of the animals in the case of the fibula and the fourth metacarpal bone (b value = 0.98), and more slowly in the case of the metatarsal bone, the third metacarpal bone, and the tibia bone (values of the b ratio 0.81–0.85), and the slowest femur, humerus and rib (value of b = 0.60–0.66). Bone stiffness increased as animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. Abstract 12 The rate of change in the value of this indicator changed at a faster rate than the increase in weight of pigs in the case of metacarpal and metatarsal bones (coefficient b = 1.01–1.22), slightly slower in the case of fibula (coefficient b = 0.92), definitely slower in the case of the tibia (b = 0.73), ribs (b = 0.66), femur (b = 0.59) and humerus (b = 0.50). Bone strength increased as animals grew. Regardless of the growth point tested, bone strength was as follows femur > tibia > humerus > 4 metacarpal> 3 metacarpal> 3 metatarsal > 4 metatarsal > rib> fibula. The rate of increase in strength of all examined bones was greater than the rate of weight gain of pigs (value of the coefficient b = 2.04–3.26). As the animals grew, the bone density increased. However, the growth rate of this indicator for the majority of bones was slower than the rate of weight gain (the value of the coefficient b ranged from 0.37 – humerus to 0.84 – fibula). The exception was the rib, whose density increased at a similar pace increasing the body weight of animals (value of the coefficient b = 0.97). The study on the influence of the breed and the feeding intensity on bone characteristics (physical and biomechanical) was performed on pigs of the breeds Duroc, Pietrain, and synthetic 990 during a growth period of 15 to 70 kg body weight. Animals were fed ad libitum or dosed system. After slaughter at a body weight of 70 kg, three bones were taken from the right half-carcass: femur, three metatarsal, and three metacarpal and subjected to the determinations described in the methodology. The weight of bones of animals fed aa libitum was significantly lower than in pigs fed restrictively All bones of Duroc breed were significantly heavier and longer than Pietrain and 990 pig bones. The average values of bending force for the examined bones took the following order: III metatarsal bone (63.5 kg) <III metacarpal bone (77.9 kg) <femur (271.5 kg). The feeding system and breed of pigs had no significant effect on the value of this indicator. The average values of the bones strength took the following order: III metatarsal bone (92.6 kg) <III metacarpal (107.2 kg) <femur (353.1 kg). Feeding intensity and breed of animals had no significant effect on the value of this feature of the bones tested. The average bone density took the following order: femur (1.23 g/cm3) <III metatarsal bone (1.26 g/cm3) <III metacarpal bone (1.34 g / cm3). The density of bones of animals fed aa libitum was higher (P<0.01) than in animals fed with a dosing system. The density of examined bones within the breeds took the following order: Pietrain race> line 990> Duroc race. The differences between the “extreme” breeds were: 7.2% (III metatarsal bone), 8.3% (III metacarpal bone), 8.4% (femur). Abstract 13 The average bone stiffness took the following order: III metatarsal bone (35.1 kg/mm) <III metacarpus (41.5 kg/mm) <femur (60.5 kg/mm). This indicator did not differ between the groups of pigs fed at different intensity, except for the metacarpal bone, which was more stiffer in pigs fed aa libitum (P<0.05). The femur of animals fed ad libitum showed a tendency (P<0.09) to be more stiffer and a force of 4.5 kg required for its displacement by 1 mm. Breed differences in stiffness were found for the femur (P <0.05) and III metacarpal bone (P <0.05). For femur, the highest value of this indicator was found in Pietrain pigs (64.5 kg/mm), lower in pigs of 990 line (61.6 kg/mm) and the lowest in Duroc pigs (55.3 kg/mm). In turn, the 3rd metacarpal bone of Duroc and Pietrain pigs had similar stiffness (39.0 and 40.0 kg/mm respectively) and was smaller than that of line 990 pigs (45.4 kg/mm). The thickness of the cortical bone layer took the following order: III metatarsal bone (2.25 mm) <III metacarpal bone (2.41 mm) <femur (5.12 mm). The feeding system did not affect this indicator. Breed differences (P <0.05) for this trait were found only for the femur bone: Duroc (5.42 mm)> line 990 (5.13 mm)> Pietrain (4.81 mm). The cross sectional area of the examined bones was arranged in the following order: III metatarsal bone (84 mm2) <III metacarpal bone (90 mm2) <femur (286 mm2). The feeding system had no effect on the value of this bone trait, with the exception of the femur, which in animals fed the dosing system was 4.7% higher (P<0.05) than in pigs fed ad libitum. Breed differences (P<0.01) in the coross sectional area were found only in femur and III metatarsal bone. The value of this indicator was the highest in Duroc pigs, lower in 990 animals and the lowest in Pietrain pigs. The cortical index of individual bones was in the following order: III metatarsal bone (31.86) <III metacarpal bone (33.86) <femur (44.75). However, its value did not significantly depend on the intensity of feeding or the breed of pigs.
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